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ecoplanet builds the operating system for the energy transition, helping European businesses cut energy costs and manage energy operations efficiently. The company is ~40 people, backed by EQT Ventures and HV Capital.
You will build and run the platform that the entire product sits on: event streams, backend services, and cloud infrastructure. Meter readings arrive from industrial sites across Europe via messages and APIs, and your role ensures this traffic lands reliably, moves through the system in a usable shape for other teams, and scales as the number of sites grows.
You'll join a 12-person engineering team organized in two squads, with real ownership and the ability to ship features to customers in weeks rather than quarters.
**Key Responsibilities:**
- **Event Streaming:** Own Kafka topic and schema design, partitioning, retention, and delivery semantics. Handle the production reality: consumers falling behind, replays, backfills, late and duplicated readings.
- **Backend Services in TypeScript:** Build ingestion services, integrations, and APIs around the event stream. Each industrial site is different; your job is turning that variety into one consistent interface that product squads can rely on.
- **Cloud Infrastructure on GCP:** Manage compute, networking, IAM, infrastructure as code, CI/CD, and observability. Build a "paved road" so other engineers can ship and debug their own services independently.
- **Technical Direction:** Set platform investment priorities, decide what to standardize, and guide the team on architectural decisions.
**Requirements:**
- At least 6–8 years building and running backend systems in production, including real-time systems in a platform or infrastructure role that other engineers depended on.
- Strong backend engineering in TypeScript: you have designed, shipped, and operated services and APIs in it (not just touched it peripherally).
- Hands-on production experience with Kafka: topic design, consumer groups, ordering, delivery guarantees, and troubleshooting (e.g., consumer groups falling behind). Comparable streaming platforms acceptable if you know them at depth.
- Solid GCP or equivalent cloud platform experience: containers, networking, IAM basics, infrastructure as code, CI/CD, monitoring and alerting. You have owned infrastructure, not just deployed onto it.
- Comfortable with high-volume time-series data: ingestion, data quality, backfills, and handling late, missing, and duplicated readings.
- Enough production experience to know which trade-offs have long-term consequences, when the boring option is right, and how to make decisions with incomplete information.
- Kubernetes knowledge at the level of running it, not just deploying to it.
- Clear written and spoken English; German is a plus.
**Nice to Have:**
- Experience in energy, industrial, IoT, or domains where data comes from real hardware.
- Knowledge of metering/device protocols, telemetry at scale, or streaming pipelines.
- Proficiency in a second programming language (Python, Go, Kotlin).
- Ownership mindset: you monitor and alert on what you build, and debug production issues as needed.
